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Library of Congress Cataloging‐in‐Publication Data
Names: Gupta, Bhisham C., 1942- author. | Guttman, Irwin, author. |
Jayalath, Kalanka P., author.
Title: Statistics and probability with applications for engineers and
scientists using Minitab, R and JMP / Bhisham C. Gupta, Irwin Guttman,
Kalanka P. Jayalath.
Other titles: Statistics and probability with applications for engineers
and scientists
Description: Second edition. | Hoboken : Wiley, 2020. | Revision of:
Statistics and probability with applications for engineers and
scientists. 2013. | Includes bibliographical references and index.
Identifiers: LCCN 2019035384 (print) | LCCN 2019035385 (ebook) | ISBN
9781119516637 (cloth) | ISBN 9781119516644 (adobe pdf) | ISBN
9781119516620 (epub)
Subjects: LCSH: Probabilities. | Mathematical statistics.
Classification: LCC QA273 .G85 2020 (print) | LCC QA273 (ebook) | DDC
519.5–dc23
LC record available at https://lccn.loc.gov/2019035384
LC ebook record available at https://lccn.loc.gov/2019035385
Cover Design: Wiley
Cover Image: © ioat/Shutterstock
In the loving memory of my parents, Roshan Lal and Sodhan Devi
‐Bhisham
In the loving memory of my parents, Anna and Samuel Guttman
‐Irwin
In the loving memory of my parents, Premadasa Jayalath and Chandra Unanthanna
‐Kalanka
Modern statisticians are familiar with the notion that any finite body of data contains only a limited amount of information on any point under examination; that this limit is set by the nature of the data themselves, and cannot be increased by any amount of ingenuity expended in their statistical examination: that the statistician's task, in fact, is limited to the extraction of the whole of the available information on any particular issue.
R. A. Fisher
Preface
AUDIENCE
This is an introductory textbook in applied statistics and probability for undergraduate students in engineering and the natural sciences. It begins at a level suitable for those with no previous exposure to probability and statistics and carries the reader through to a level of proficiency in various techniques of statistics. This text is divided into two parts: Part I discusses descriptive statistics, concepts of probability, probability distributions, sampling distributions, estimation, and testing of hypotheses, and Part II discusses various topics of applied statistics, including some reliability theory, data mining, cluster analysis, some nonparametric techniques, categorical data analysis, simple and multiple linear regression analysis, design and analysis of variance with emphasis on
This text is suitable for a one‐ or two‐semester undergraduate course sequence. The presentation of material gives instructors a lot of flexibility to pick and choose topics they feel should make up the coverage of material for their courses. However, we feel that in the first course for engineers and science majors, one may cover Chapter 1 and 2, a brief discussion of probability in 3, selected discrete and continuous distributions from Chapter 4 and 5 with more emphasis on normal distribution, Chapter 7–9, and couple of topics from Part II that meet the needs and interests of the particular group of students. For example, some discussion of the material
